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Kirill Tamogashev

4 accepted papers

2026

Discrete Diffusion Samplers and Bridges: Off-Policy Algorithms and Applications in Latent Spaces

ICML 2026poster

Sampling from a distribution $p(x) \propto e^{-\mathcal{E}(x)}$ known up to a normalising constant is an important and challenging problem in statistics. Recent years have seen the rise of a new family of amortised sampling algorithms, commonly referred to as diffusion samplers, that enable fast and…

Cited by 0SourceScholar
2026

Multi-Marginal Flow Matching with Adversarially Learnt Interpolants

ICLR 2026poster

Learning the dynamics of a process given sampled observations at several time points is an important but difficult task in many scientific applications. When no ground-truth trajectories are available, but one has only snapshots of data taken at discrete time steps, the problem of modelling the dyna…

Cited by 0SourcecodeScholar
2024

FINALLY: fast and universal speech enhancement with studio-like quality

NeurIPS 2024poster

In this paper, we address the challenge of speech enhancement in real-world recordings, which often contain various forms of distortion, such as background noise, reverberation, and microphone artifacts. We revisit the use of Generative Adversarial Networks (GANs) for speech enhancement and theoreti…